Regularized methods for efficient ranking in networks
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Updated
Jun 20, 2024 - Python
Regularized methods for efficient ranking in networks
Rank a Table Based Off Given Parameters
A bridge finder for the card 'Small World' in the card game 'Yu-Gi-Oh!'.
LibAUC: A Deep Learning Library for X-Risk Optimization
Code for the paper Prediction-Powered Ranking of Large Language Models, Arxiv 2024.
LTR with gradient boosting
A Python 3.12 implementation of the Schulze method for ranking candidates.
A Bayesian Model to Rank Tennis Players
League ranking for arbitrary numbers of competitors.
recommendation generation and ranking model
The Plum Book is a recruiting tool. It takes the honor roole data available in the newspaper, cleans it, and adds it in a database. This is then presneted in a treeview wtih options to search, edit, delete, or add to the database. Finally, data for each student queried form the database, and ranked as the "plums" of that year.
get an overall ranking score for a business from various resources
Code and Supplementary Material to the Paper: Pairwise Learning to Rank by Neural Networks Revisited: Reconstruction, Theoretical Analysis and Practical Performance
Minimal Informaition Retrival System and Ranking for Results using Python
Django based website to filter publications made online via the arXiv.org API
rec_pangu is a flexible open-source project for recommendation systems. It incorporates diverse AI models like ranking algorithms, sequence recall, multi-interest models, and graph-based techniques. Designed for both beginners and advanced users, it enables rapid construction of efficient, custom recommendation engines.
RankIt is a customizable ranking system implemented in Python that uses the TOPSIS method to assign scores to a given set of items and rank them based on these scores.
A Python-based command-line tool developed as part of a research project on Machine Learning and IoT. It utilizes a custom implementation of the TF-IDF algorithm to provide interactive and concise three-point answers to IoT-related queries.
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